Method and device for adjusting a power allocation of users in a digital subscriber line environment

ABSTRACT

A method and a device adjust a power allocation of users in a digital subscriber line environment. An intermediate power allocation is determined for at least one user initializing with the digital subscriber line environment based on a new power allocation determined for the digital subscriber line environment containing the at least one user. The intermediate power allocation provides a predefined minimum signal-to-noise ratio margin for the active users of the digital subscriber line environment. Furthermore, a communication system can contain such a device.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation, under 35 U.S.C. §120, of copendingpatent application Ser. No. 13/697,644, filed Jan. 25, 2013, which was a§371 of international application No. PCT/EP2010/056577, filed May 12,2010, which designated the United States; the prior applications areherewith incorporated by reference in their entirety.

BACKGROUND OF THE INVENTION Field of the Invention

The invention relates to a method and to a device for adjusting a powerallocation of users in a digital subscriber line environment. Inaddition, a system comprising at least one such device is suggested.

DSL or xDSL, is a family of technologies that provide digital datatransmission in particular over wires of a local telephone network.

High speed Internet access is gaining importance and can be via xDSLservices using existing copper lines. Also, other applications emergethat require broadband transmission services, e.g., triple play offerscomprising subscriber access to Internet, TV and voice datatransmission. A bandwidth consuming application is the transmission ofTV data via xDSL, wherein one HDTV channel may require a data rateamounting to 12 Mbit/s.

Therefore, requirements for high speed Internet access are increasing.Operators are optimizing services that are offered to their customers.This becomes a difficult task as an increasing amount of users as wellas high data rates leads to higher crosstalk between subscriber lines ina cable binder. In most cases, crosstalk noise limits the performance.However, also crosstalk noise may vary over time: There may be lowcrosstalk noise when a significant amount of customers have switched offtheir equipment and there may be a considerable amount of crosstalknoise during business hours when the majority of customers use theirdevices.

FIG. 1 shows a schematic diagram of a cable or binder 101 comprisingseveral lines 102, 103 of a DSL system. The lines 102 and 103 areconnected at one side to a DSLAM 104 that could be deployed at a centraloffice or at a remote terminal and on the other side the line 102 isconnected to a CPE 105 and the line 103 is connected to a CPE 106.

Crosstalk occurs between the lines 102 and 103 that are coupled by thebinder 101: The crosstalk comprises a near-end crosstalk (NEXT) 107 and108 as well as far-end crosstalk (FEXT) 109 and 110.

Such crosstalk is perceived at a receiver of a victim (coupled) line asnoise and therefore decreases a signal-to-noise ratio (SNR) at thisreceiver thereby reducing an attainable data rate on this line.

The twisted pair communication channel is frequency selective, i.e. thedirect channel attenuates higher frequencies more than lowerfrequencies, but the electromagnetic coupling between twisted pair linesprovides higher crosstalk with increasing frequency.

xDSL systems employing multi-carrier modulation schemes like DiscreteMulti-Tone (DMT) are able to flexibly shape their transmit powerspectrum in order to adapt to frequency-selective characteristics of thechannel. Dynamic Spectrum Management (DSM) Level 2 is an approach toimprove an overall system performance by centrally shaping transmitspectra (which corresponds to shaping of power allocations) ofinterfering lines so that a performance loss due to crosstalk effects isminimized. With enough (in particular full) knowledge about the channelcharacteristics, a Spectrum Management Center (SMC) is able to computean optimal power allocation for each user and reports these allocationsto the individual modems, which utilize the power allocation determinedby the SMC to configure a transmit power level for each tone (of the DMTmodulation scheme).

FIG. 2 shows a schematic diagram of an optimal downstream powerallocation for a VDSL2 system with two users (with different looplengths amounting to 300 m for the first user and to 600 m for thesecond user) determined by a SMC using DSM. It is noted that user inthis regard may in particular refer to a CPE or a terminal. The user mayin particular be a DSL modem. Hence, FIG. 2 comprises a power spectrumdensity (PSD) mask 201 which can be utilized by both users, wherein aPSD allocation of the first user (the 300 m user) is indicated by agraph 202 and a PSD allocation of the second user (the 600 m user) isindicated by a graph 203.

The SMC assigns the frequency band above ca. 8 MHz exclusively to the300 m user (see graph 202), because the 600 m user (see graph 203)cannot efficiently transmit data at this range due to high directchannel attenuation. In a range below 8 MHz, the SMC instructs the 300 muser (see graph 202) to reduce its transmit power in order to limit itsinterference with the 600 m user.

The power allocation provided by the SMC may provide a target SNRmargin, which protects the users of the DSM system from (arbitrary ornot expected) noise fluctuations, e.g., crosstalk from legacy systems orother interferers. In this regard, a target margin of, e.g., 6 dB can beprovided to ensure a specified service quality, i.e. bit-error-ratio(BER) and data rate. Hence, the actual noise may increase by up to 6 dBrelative to the noise level that has been assumed by the SMC whencomputing the power allocations.

FEXT between copper wires in a binder is the dominant impairment incurrent DSL systems, severely limiting achievable data rates. DSM Level2 tries to mitigate the capacity loss due to crosstalk by centrallycoordinating the modem's transmit power allocation, effectivelyintroducing politeness between users. Existing solutions, however arenot able to cope with a scenario that some optimal joint powerallocation computed by an SMC according to current channel conditionsmay become invalid at some point in the future when the channel or DSMsystem parameters change, e.g.,

-   -   (a) when a user joins or leaves the system. This is likely to        happen in an unbundled environment where customers change        service providers, which operate their proprietary DSM system.    -   (b) when a user changes a service. If a user upgrades, e.g.,        from an ADSL2 service to a VDSL2 service, the transmit spectrum        will change thereby affecting the crosstalk profile on other        users' lines in the binder.

In any such event, the SMC has to determine a new joint allocation thatcorresponds to the new situation. However, it is a significant problemthat transmit spectra of modems that are already active (in show-time)cannot be reconfigured without interrupting their service, which in mostcases is inacceptable and should therefore be avoided. Instead, updatingthe transmit power profile is thus delayed until a modem enters a(re-)initialization phase.

However, updating spectra for a part of the users only leads to a powerallocation comprising a mixture of merely partially optimized spectra.Such mixture bears the risk that a desired target BER cannot beguaranteed as long as the final state of the new power allocation is notreached, i.e. as long as not all modems have been re-initializedaccording to the new power allocation. Until such final state isreached, it is likely to obtain severe drops of the SNR margin thusseriously affecting an overall line stability.

BRIEF SUMMARY OF THE INVENTION

It is accordingly an object of the invention to provide a method whichovercomes the disadvantages of the heretofore-known devices of thisgeneral type and which provides for an efficient solution to adapt powerallocations in a DSM system.

This problem is solved according to the features of the independentclaims. Further embodiments result from the depending claims.

In order to overcome this problem, a method is provided for adjusting apower allocation of users in a digital subscriber line environment,

wherein an intermediate power allocation is determined for at least oneuser initializing with the digital subscriber line environment based ona new power allocation determined for the digital subscriber lineenvironment comprising this at least one user;

wherein the intermediate power allocation provides a predefined minimumSNR margin for the active users of the digital subscriber lineenvironment.

It is noted that the new power allocation corresponds to a target powerallocation value comprising in particular a power spectrum densitydistribution over a frequency range. It is also noted that the powerallocation can be also referred to as a (e.g., transmit) spectrum.

It is further noted that user refers to a terminal, a CPE or a modem.The user can be initialized to become an active user (i.e. to enter anactive mode, also referred to as “show-time”).

Advantageously, said minimum SNR margin can be provided for all activeusers of the digital subscriber line environment, i.e. for all usersthat are in show-time. Hence, the PSD of the at least one user thatjoins the digital subscriber line environment is adjusted such that itconverges towards the new power allocation and that it does notinterfere with already active users in a way that their SNR drops belowsaid minimum SNR margin. The intermediate power allocations (of thetransition phase towards the new power allocation) can be determinedsuch that an SNR margin for all users does not fall below saidpredefined minimum SNR margin.

Via said intermediate power allocation, a transition is provided thatallows the DSL environment to gradually adjust to and eventually reachthe new power allocation without a significant impairment to existingusers.

Hence, the solution provided allows to gradually update powerallocations in a DSM system and assures that at each point during suchgradual transition, an actual SNR margin for each user does not fallbelow a given minimum value.

Advantageously, only transmit spectra (or power allocations) of usersinitializing a new session are modified and a forced retraining canlargely be avoided.

In an embodiment, at least one intermediate power allocation isdetermined that converges towards the new power allocation.

In particular, with at least one user that is about to (re-)initializewith the DSL environment, an(other) intermediate power allocation stagecan be determined. Hence, the approach can be iteratively applied toconverge via several intermediate power allocations toward the new(target) power allocation.

It is noted that initializing refers to a user that wants to getconnected (or re-connected) to the DSL environment.

The updating scheme suggested advantageously updates or adjusts thepower allocation if a user (re-)initializes a new session.

In another embodiment, the digital subscriber line environment comprisesat least one DSM system, which is managed by an SMC.

The SMC may be a centralized component that provides the adjustment ofpower allocations. Also the SMC may be realized as at least one physicalentity or it may be combined with an existing physical entity.

In a further embodiment, the predefined minimum SNR margin can beprovided for the intermediate power allocation or individually for eachuser for which the intermediate power allocation is determined or forevery subcarrier or a portion of users or subcarriers.

In a next embodiment, the intermediate power allocation is determinedutilizing spectral limitation masks as well as a limited power budgetper the at least one user, which limited power budget is in particulardistributed among tones of a DMT modulation scheme.

It is also an embodiment that the intermediate power allocation isdetermined such that a distance metric between an actual powerallocation and the new power allocation is reduced, in particularminimized.

Pursuant to another embodiment, the distance metric is reduced meetingat least one of the following constraints:

-   -   a total transmit power is limited;    -   a transmit power on each sub-carrier or tone is limited        individually by a power spectrum density mask;    -   for the minimum SNR margin, a data rate achieved by each user        with the obtained power allocation equals or exceeds a        predetermined target data rate.

In a next embodiment, the distance metric according to Δ(s(i), s_(new))comprises at least one of the properties:

-   -   Δ is convex in s_(k) ^(n);    -   Δ is separable in s_(k) ^(n); and    -   Δ(s(i), s_(new)) has a unique global minimum for s(i)=s_(new).

According to an embodiment, the distance metric comprises a distancefunction as follows:

${{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - 1} \right)^{2}}}},{or}$${{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}{\alpha_{k}^{n}\left( {{s_{k}^{n}(i)} - s_{k,{new}}^{n}} \right)}^{2}}}},{or}$${{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}{\alpha_{k}^{n}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - \frac{s_{k,{new}}^{n}}{s_{k}^{n}(i)}} \right)}^{2}}}},$

wherein

-   -   s_(k) ^(n) denotes a PSD of the transmit signal of a user n;    -   k determines a subchannel or tone;    -   s_(new) is the new power allocation;    -   s(i) is the intermediate power allocation at a step i.

It is noted that the term s_(k,new) ^(n) can be set to a small positivevalue. According to another embodiment, the intermediate powerallocation is determined by solving the following optimization problem:

$\begin{matrix}\min\limits_{{{s_{k}^{n}{(i)}}{\forall{n \in _{i}}}},k} & {\Delta \left( {{s(i)},s_{new}} \right)} & \; \\{s.t.} & {{R^{n}\left( \overset{\_}{\gamma} \right)}_{s{(i)}}{\geq R_{target}^{n}}} & {\forall n} \\\; & {{\sum\limits_{k}{s_{k}^{n}(i)}} \leq P_{\max}^{n}} & {\forall n} \\\; & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {{\forall n},k}\end{matrix}$

wherein

-   -   n∈G_(i) ⊂N is a user;    -   G_(i) determines a group comprising the at least one user        initializing with the digital subscriber line environment;    -   N determines the users sharing the same binder;    -   s_(k) ^(n) denotes a PSD of the transmit signal of a user n;    -   s_(k,mask) ^(n) is a PSD mask determined by a band profile used;    -   k determines a subchannel or tone;    -   s_(new) is the new power allocation;    -   s(i) is the intermediate power allocation at a step i;    -   γ is the predetermined minimum SNR margin;    -   R^(n) is a data rate of the user n;    -   R_(target) ^(n) is a target data rate of user n;    -   P_(max) ^(n) is a maximum aggregate transmit power of the user        n.

In yet another embodiment, the optimization problem is solved by a dualdecomposition combined with a convex relaxation.

According to a next embodiment, the optimization problem is solved bydecomposing a Lagrangian

$\Lambda = {{\Delta \left( {{s(i)},s_{new}} \right)} + {\sum\limits_{n}{\omega^{n}\left( {R_{target}^{n} - {R^{n}(i)}} \right)}} + {\sum\limits_{n}{\lambda^{n}\left( {{\sum\limits_{k}{s_{k}^{n}(i)}} - P_{\max}^{n}} \right)}}}$

wherein

-   -   ω^(n) is a dual variable corresponding to the data rate        constraint of user n; and    -   λ^(n) is a dual variable corresponding to the power constraint,    -   into per-tone Lagrangians Λ_(k) according to

$\mspace{79mu} {\Lambda = {{\sum\limits_{k}\Lambda_{k}} + \underset{\underset{{{const}.\mspace{14mu} {in}}\mspace{14mu} {s{(i)}}}{}}{{\sum\limits_{n}{\omega^{n}R_{target}^{n}}} - {\sum\limits_{n}{\lambda^{n}P_{\max}^{n}}}}}}$     with$\Lambda_{k} = {{\sum\limits_{n}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - 1} \right)^{2}} + {\sum\limits_{n}{\lambda^{n}{s_{k}^{n}(i)}}} - {f_{s}{\sum\limits_{n}{\omega^{n}{{\log_{2}\left( {1 + {\frac{1}{\overset{\_}{\gamma}\Gamma}\frac{g_{k}^{n,n}{s_{k}^{n}(i)}}{{\sum\limits_{m \neq n}{g_{k}^{n,m}{s_{k}^{m}(i)}}} + \sigma_{k}^{2}}}} \right)}.}}}}}$

Pursuant to yet an embodiment, a dual problem

$\begin{matrix}{\max\limits_{\omega^{n},{\lambda^{n}{\forall{n \in _{i}}}}}\min\limits_{{{s_{k}^{n}{(i)}}{\forall{n \in _{i}}}},k}} & \Lambda & \; \\{s.t.} & {\omega^{n},{\lambda^{n} \geq 0}} & {\forall n} \\\; & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {{\forall n},k}\end{matrix}$

-   -   of the optimization problem is solved by solving K independent        sub-problems

$\begin{matrix}\min\limits_{{s_{k}^{n}{(i)}}{\forall{n \in _{i}}}} & \Lambda_{k} & \; \\{s.t.} & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {\forall n}\end{matrix}$

-   -   per Lagrange multiplier search step.

Hence, this approach renders the overall algorithm complexity linear inK.

According to another embodiment,

-   -   at an initial step i=0, it is determined whether the minimum SNR        margin γ with 1≦ γ≦γ_(target) exists so that the optimization        problem is feasible for s(0);    -   wherein in case such minimum SNR margin γ exists, this value is        used to determine the at least one intermediate power        allocation;    -   wherein in case no such minimum SNR margin γ≧1 (0 dB) exists,        the set G₀ is augmented by at least one additional user whose        power allocation is re-shaped at the time instant t=t₀.

By enlarging the set of feasible power allocations, a low intermediateminimum SNR margin γ increases the flexibility of shaping the powerallocations and thus tends to reduce the number of required intermediatesteps i before all users reach the value of the new (target) powerallocation s_(new). Hence, a trade-off decision can be made between afaster convergence and a reduced protection against fluctuation ofnoise.

In the latter case (in case no such minimum SNR margin γ≧1 exists), aforced resynchronization of these augmented users can be conducted.

The problem stated above is also solved by a device comprising or beingassociated with a processing unit that is arranged such that the methodas described herein is executable thereon.

It is further noted that said processing unit can comprise at least one,in particular several means that are arranged to execute the steps ofthe method described herein. The means may be logically or physicallyseparated; in particular several logically separate means could becombined in at least one physical unit.

Said processing unit may comprise at least one of the following: aprocessor, a microcontroller, a hard-wired circuit, an ASIC, an FPGA, alogic device.

Pursuant to an embodiment, the device is a modem, a DSLAM or acentralized network component, in particular a spectrum managementcenter.

The solution provided herein further comprises a computer programproduct directly loadable into a memory of a digital computer,comprising software code portions for performing the steps of the methodas described herein.

In addition, the problem stated above is solved by a computer-readablemedium, e.g., storage of any kind, having computer-executableinstructions adapted to cause a computer system to perform the method asdescribed herein.

Furthermore, the problem stated above is solved by a communicationsystem comprising at least one device as described herein.

Embodiments of the invention are shown and illustrated in the followingfigures.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING

FIG. 1 is a schematic diagram of a cable having several lines;

FIG. 2 is a schematic diagram of an optimal downstream power allocationfor a VDSL2 system with two users;

FIG. 3 shows a schematic diagram of a transition of a multi-user powerallocation after a user 3 has joined the DSM system at a time instancet=t₀;

FIG. 4 shows a diagram visualizing a PSD over a frequency, wherein a PSDmask provides an admissible power allocation range, which is utilized bythree users at an initial power allocation state s_(old);

FIG. 5 shows based on FIG. 4 a new (target) power allocation s_(new) incase an additional user joins the DSM system;

FIG. 6 shows based on FIG. 4 an intermediate power allocation s(i) thatallows adjusting the DSM system towards the new power allocations_(new), but avoids a re-configuration of users that are still active(in show-time) and provides sufficient SNR margin to allow the DSMsystem to efficiently maintain its operation.

DESCRIPTION OF THE INVENTION

The solution provided herewith suggests determining intermediate powerallocations for users initializing a new session and to provide afavorable transition phase so that the xDSL system can eventually reacha new (target) multi-user power allocation that may be determined by anSMC.

It is noted that the power allocation is also referred to as a(transmit) spectrum. A user referred to herein may also be regarded asterminal, CPE or modem (or vice versa).

The intermediate power allocations (of the transition phase towards thenew power allocation) can be determined such that an SNR margin for allusers does not fall below a predefined threshold.

The updating scheme suggested in particular updates or adjusts the powerallocation if a user (modem) initializes a new session. Hence, forcedretraining of modems can be largely avoided. The intermediate powerallocations can be determined utilizing spectral limitation masks aswell as a limited power budget per modem, which is distributed amongtones of a DMT modulation scheme.

Overview: Determining Intermediate Power Allocations

The solution provided in particular utilizes the following input:

-   -   (a) a new (target, multi-user) power allocation s_(new) to which        all users should eventually be updated; and    -   (b) a minimum SNR margin γ.

At each time instance when at least one user is about to initialize anew session, a (further) intermediate power allocation for this at leastone user is determined such that a distance metric between theintermediate (multi-user) power allocation and the new power allocations_(new) is reduced, in particular minimized and at least one of thefollowing constraints can be met:

-   -   (a) a total transmit power is limited;    -   (b) a transmit power on each sub-carrier (DMT tone) is limited        individually by a PSD mask;    -   (c) for a given minimum SNR margin γ a data rate achieved by        each user with the obtained power allocation equals or exceeds a        predetermined target data rate.

These constraints lead to an optimization problem (details, see belowwith regard to equation (14)), which can be solved in an efficientmanner by a dual decomposition approach combined with a convexrelaxation technique.

The minimum SNR margin γ may be chosen individually for everyoptimization stage, for every subcarrier (or a portion thereof) and/orindividually for each user whose transmit spectrum is to be(re-)computed.

FIG. 4 shows a (downstream) multi-user power allocation at an initialstate, also referred to as power allocation s_(old) for a DSM systemcomprising three VDSL users with loop lengths of X meters, wherein Xamounts to 400, 800 and 1000. The respective user is also referred to asthe X m user. Hence, FIG. 4 depicts a PSD mask 405 and power allocationsfor the 400 m user 401, the 800 m user 403 and the 1000 m user 404.

At a time instance t=t₀, a new user, also referred to as 600 m user 402(because of its loop length amounting to 600 m) joins the DSM system andstarts a new session so that the SMC has to re-calculate the powerallocation, i.e. determine the new optimized allocation s_(new) for the4-user system. Such new power allocation s_(new) is shown in FIG. 5. Itis noted that both power allocations s_(old) and s_(new) provide atarget SNR margin amounting to 6 dB.

In case the 400 m user 401, the 800 m user 403 and the 1000 m user 404users are already in show-time at the time instance t=t₀, they cannot beupdated instantly to the new power allocation s_(new) without causing aninterruption of service. Hence, these 401, 403 and 404 users aregradually updated, i.e. an update for the user in show-time is delayeduntil this user conducts a re-initialization phase for a next session.

On the other hand, the power allocation for the newly joined 600 m user402 cannot immediately be configured to the new power allocation s_(new)without the risk of causing a severe drop of the SNR margin to any (orto all) of the 4 users. Therefore, an intermediate power allocation s(i)is determined as shown in FIG. 6 for this 600 m user 402 to be appliedat the time instance t=t₀, which guarantees that all users operate withan SNR margin equal or above a given SNR minimum margin (which can beset to, e.g., 2 dB). Also, the spectrum allocated for the 600 m user 402for this intermediate power allocation s(i) is selected to convergetowards the new power allocation s_(new); the other users (which are inshow-time according to this example) maintain operation with theirpreviously set configurations. The same procedure can then iterativelybe applied to each user starting a new session after this time instancet=t₀ until the entire DSM system reaches and utilizes the new powerallocation s_(new). In practice, this may require for some usersmultiple intermediate transmit power allocations until the DSM systemreaches said new power allocation s_(new).

System Model for a Static Scenario

A channel model for a static DSL system comprises a set N of userssharing the same binder, thus causing mutual FEXT on each other's lines.By employing DMT transmission with K orthogonal tones k=1, . . . , K,the interference channel is divided into K independent subchannels k.Applying a sufficiently small tone spacing Δf, the direct channel ofuser n∈N on tone k can be described by a single complex coefficienth_(k) ^(n,n). Similarly, a crosstalk channel from a disturber m to avictim line n on the tone k can be given by a complex scalar h_(k)^(n,m) (m≠n).

The term s_(k) ^(n) denotes a PSD of the transmit signal of a user n andσ_(k) ² denotes a combined PSD of alien FEXT and receiver backgroundnoise on the tone k.

Using a Shannon gap approximation, a number of bits b_(k) ^(n)(γ) persymbol that a user n can load onto the tone k with a given SNR marginγ≧1 amounts to

$\begin{matrix}{{{b_{k}^{n}(\gamma)} = {\log_{2}\left( {1 + {\frac{1}{\gamma\Gamma}\frac{g_{k}^{n,n}s_{k}^{n}}{{\sum\limits_{m \neq n}{g_{k}^{n,m}s_{k}^{m}}} + \sigma_{k}^{2}}}} \right)}},} & (1)\end{matrix}$

where

-   -   Γ>1 denotes a so-called gap to capacity, which is a function of        a target BER;    -   θ_(k) ^(n,m)=|h_(k) ^(n,m)|² are the crosstalk and direct        channel gain coefficients.        Furthermore, a total utilized power P^(n) and a data rate R^(n)        of the user n, are given by

$\begin{matrix}{{P^{n} = {\Delta \; f{\sum\limits_{k}s_{k}^{n}}}}{and}} & (2) \\{{{R^{n}(\gamma)} = {f_{s}{\sum\limits_{k}{b_{k}^{n}(\gamma)}}}},} & (3)\end{matrix}$

respectively, where f_(s) is a symbol rate of the DMT system.

Update of Multi-User Power Allocation in a Non-Static Scenario

In a DSM system, regardless whether operating in rate-adaptive,margin-adaptive or fixed-margin mode, the optimal joint power allocationis determined using a spectrum balancing algorithm which typicallyaccounts for at least three per-user constraints in the optimizationprocess:

-   (a) A total power constraint

P ^(n) ≦P _(max) ^(n) ∀n,  (4)

-   -   where P_(max) ^(n) is a maximum aggregate transmit power        specified in the respective xDSL standard;

-   (b) A spectral mask constraint

0≦s _(k) ^(n) ≦s _(k,mask) ^(n) ∀n,k,  (5)

-   -   where s_(k,mask) ^(n) is a PSD mask determined by a band profile        used; and

-   (c) A rate constraint

R ^(n)(γ)≧R _(target) ^(n) ∀n,  (6)

-   -   where R_(target) ^(n) is a target data rate of user n chosen        according to a Service Level Agreement and γ amounts to a value        γ_(target)>1 which is a target SNR margin selected by the        provider.

Next, a non-static scenario is considered in which an optimized powerallocation

s _(old)={_(k,old) ^(n) |n∈N;k=1, . . . ,K},  (7)

computed by the SMC becomes invalid at some time instance t=t₀ when auser joins or leaves the DSM system or in case a user changes theservice. In this case, a new power allocation

s _(new) ={s _(k,new) ^(n) |n∈N;k=1, . . . ,K}  (8)

is required, which is optimized for a time t≧t₀, but cannot be appliedfor those users that are already in show-time without interrupting theirservice.

FIG. 3 shows a schematic diagram of a transition of a multi-user powerallocation after a user 3 (n*=3) has joined the DSM system at a timeinstance t=t₀. The new power allocation is determined such that theconstraints according to equations (4) and (6) are met for all users n∈Nwith N={1,2,3}; the constraints according to equations (4) and (6) aremet for the old power allocation s_(old) for users n∈{1,2} without theuser n*(user 3) being active prior to the instant of time t<t₀, i.e. thePSD s_(k,old) ^(n*)=0∀k.

If all users n≠n* are already in show-time at the time instant t=t₀,only the transmit PSD s_(k) ^(n*) of this newly joined user n* can beupdated.

Time instances or steps i=0, 1, 2, . . . are defined in a discrete timerange corresponding to time instances t=t_(i) (t_(i)<t_(i+1)) in acontinuous time range at which point any of the users initiates a newsession and therefore its transmit PSD can be re-configured towards thenew power allocation s_(new).

In addition,

s(i)={s _(k) ^(n)(i)|n∈N;k=1, . . . ,K}  (9)

denotes a power allocation used by the system during an intermediatetime interval θ_(i)=t_(i)≦t<t_(i+1). Hence, if a user n is notre-initialized at an instance i, no convergence towards the new powerallocation s_(new) is reached, i.e. s_(k) ^(n)(i)=s_(k) ^(n)(i−1)∀k.

In order to achieve an intermediate power allocation that convergestoward the new power allocation s_(new), the user n*'s PSD s_(k)^(n*)(0) could be initialized at an instance i=0 to correspond to thenew optimal allocation s_(k,new) ^(n*), while the other users n≠n*maintain transmission with the previously determined (then optimal)spectra, i.e.

$\begin{matrix}{{s_{k}^{n}(0)} = \left\{ {{{\begin{matrix}s_{k,{new}}^{n} & {n = n^{*}} \\s_{k,{old}}^{n} & {n \neq n^{*}}\end{matrix}{\forall k}} = 1},\ldots \mspace{14mu},{K.}} \right.} & (10)\end{matrix}$

At a next instance i=1, a user 2 is re-initialized and its transmit PSDs_(k) ²(1) could be set to s_(k,new) ², wherein the other users maintaintheir spectra (as they are still in show-time), i.e.

$\begin{matrix}{{s_{k}^{n}(1)} = \left\{ {{{\begin{matrix}s_{k,{new}}^{n} & {n = 3} \\{s_{k}^{n}(0)} & {n \neq 3}\end{matrix}{\forall k}} = 1},\ldots \mspace{14mu},{K.}} \right.} & (11)\end{matrix}$

If each user has been re-initialized, e.g., at least one time, the DSMsystem is fully updated and has reached its new power allocations_(new).

On the other hand, during the transition phase described, another eventcould invalidate the previously determined new power allocation s_(new).In this case, a revised a new optimal power allocation s_(new) may bedetermined and the power allocation s_(old) is set to the current powerallocation.

During each interval θ_(i), an actual SNR margin γ^(n)(i) of the user nresulting from a given multi-user power allocation s(i) can be obtainedby solving the equation

R ^(n)(γ^(n)(i))|_(s(i)) −R _(target) ^(n)=0,  (12)

However, it cannot be guaranteed that any of the intermediateallocations s(i), which are a mixture of old and new optimized powerspectra, are feasible, i.e. yield a solution γ^(n)(i)≧1 for equation(12).

Proposal for New Updating Scheme

An approach is suggested that enables seamless transition from the oldpower allocation s_(old) to the new power allocation s_(new) in the DSMsystem. Hence, intermediate power allocations s(i) are determined suchthat at all times the actual SNR margin γ^(n)(i) is guaranteed not tofall below a specified minimum value γ. This can in particular beachieved by shaping the intermediate spectra s(i) at each instance itowards (in particular as similar as possible) the new (target) powerallocation s_(new), while accounting for per-user power and target rateconstraints. Such similarity between the intermediate power allocations(i) and the new (target) power allocation s_(new) can be determinedbased on a distance function

$\begin{matrix}{{{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - 1} \right)^{2}}}},{or}} & \left( {13a} \right) \\{{{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}{\alpha_{k}^{n}\left( {{s_{k}^{n}(i)} - s_{k,{new}}^{n}} \right)}^{2}}}},{or}} & \left( {13b} \right) \\{{{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}{\alpha_{k}^{n}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - \frac{s_{k,{new}}^{n}}{s_{k}^{n}(i)}} \right)}^{2}}}},} & \left( {13c} \right)\end{matrix}$

which reaches 0 for s(i)=s_(new).

It is noted that a distance metric according to Δ(s(i), s_(new)) maycomprise at least one of the properties:

-   -   Δ is convex in s_(k) ^(n);    -   Δ is separable in s_(k) ^(n); and    -   Δ(s(i), s_(new)) has a unique global minimum for s(i)=s_(new).

In order to avoid division by zero, the term s_(k,new) ^(n) can belower-bounded to some sufficiently small positive value s_(min). Forexample, a value of −130 dBm/Hz could be useful for DSL applications.

At an instance i, users n∈G_(i) ⊂N are about to resynchronize. Based ona predetermined minimum SNR margin γ, the intermediate power allocations(i) is obtained by solving the following optimization problem

$\begin{matrix}\begin{matrix}\min\limits_{{{s_{k}^{n}{(i)}}{\forall{n \in _{i}}}},k} & {\Delta \left( {{s(i)},s_{new}} \right)} & \; \\{{s.t.}\mspace{14mu}} & {{R^{n}\left( \overset{\_}{\gamma} \right)}_{s{(i)}}{\geq R_{target}^{n}}} & {\forall n} \\\; & {{\sum\limits_{k}{s_{k}^{n}(i)}} \leq P_{\max}^{n}} & {\forall n} \\\; & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {{\forall n},k}\end{matrix} & (14)\end{matrix}$

Wherein the spectra for users n∉G_(i) are maintained unchanged accordingto

$\begin{matrix}{{s_{k}^{n}(i)} = \left\{ {{{\begin{matrix}s_{k,{old}}^{n} & {i = 0} \\{s_{k}^{n}\left( {i - 1} \right)} & {i > 0}\end{matrix}{\forall{n \notin _{i}}}};{k = 1}},\ldots \mspace{14mu},{K.}} \right.} & (15)\end{matrix}$

An efficient solution of the problem according to equation (14) will beshown and explained below.

A convergence analysis of the proposed scheme could be summarized asfollows: Basically, a sequence of optimized power allocations {Δ(s(i),s_(new))} is monotonously decreasing, i.e.

Δ(s(i),s _(new))≦Δ(s(i−1),s _(new)).  (16)

In practical scenarios, DSL sessions are of limited (finite) durationand for every instance i with s≠s_(new), there will always be asucceeding instance j>i such that

Δ(s(j),s _(new))<Δ(s(i),s _(new)),  (17)

which implies convergence of the system to finally reach the new powerallocation s_(new) within a finite number of (time) steps.

An existence of a feasible intermediate power allocation s(i) can beshown by the following induction: If a feasible solution for theintermediate power allocation s(i) exists, this solution will also befeasible for a succeeding intermediate power allocation s(i+1). Theremaining issue is to find an initial power allocation s(0) that also isfeasible.

As discussed above, there is no guarantee that a service withpre-defined target rates and pre-defined target BER can be maintainedfor all users once the newly joined user becomes active. Thus, at theinitial step i=0, it has to be determined whether a minimum SNR margin γwith 1≦ γ≦γ_(target) exists so that equation (14) with G₀={n*} isfeasible for s(0). If such a minimum SNR margin γ is found, this valuecan be used to determine all intermediate power allocations.

By enlarging the set of feasible power allocations, a low intermediatemargin γ increases the flexibility of shaping the spectra and thus tendsto reduce the number of required intermediate steps i, before all userscan be set to the new (target) power allocation s_(new). Hence, atrade-off decision can be made between a faster convergence and areduced protection against fluctuation of noise.

If, however, no feasible γ≧1 exists, the set G₀ can be augmented by oneor more additional users whose spectra are to be re-shaped at the timeinstant t=t₀. In this case, a forced resynchronization of these usersmay be required.

Low-Complexity Solution

The objective to minimize the term Δ(s(i), s_(new)) is convex in s_(k)^(n)(i) and separable with regard to the tones k while the target rateconstraint R^(n)( γ)|_(s(i))≧R_(target) ^(n) leads to a non-convex setof feasible solutions, making it difficult to find a solution that isguaranteed to be globally optimal.

It is thus suggested to decompose a Lagrangian

$\begin{matrix}{\Lambda = {{\Delta \left( {{s(i)},s_{new}} \right)} + {\sum\limits_{n}{\omega^{n}\left( {R_{target}^{n} - {R^{n}(i)}} \right)}} + {\sum\limits_{n}{\lambda^{n}\left( {{\sum\limits_{k}{s_{k}^{n}(i)}} - P_{\max}^{n}} \right)}}}} & (18)\end{matrix}$

wherein

-   -   θ^(n) is a dual variable corresponding to the data rate        constraint of user n; and    -   λ^(n) is a dual variable corresponding to the power constraint,        into per-tone Lagrangians Λ_(k) according to

$\begin{matrix}{\mspace{79mu} {{\Lambda = {{\sum\limits_{k}\Lambda_{k}} + \underset{\underset{{{const}.\mspace{14mu} {in}}\mspace{14mu} {s{(i)}}}{}}{{\sum\limits_{n}{\omega^{n}R_{target}^{n}}} - {\sum\limits_{n}{\lambda^{n}P_{\max}^{n}}}}}}\mspace{79mu} {with}}} & (19) \\{\Lambda_{k} = {{\sum\limits_{n}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - 1} \right)^{2}} + {\sum\limits_{n}{\lambda^{n}{s_{k}^{n}(i)}}} - {f_{s}{\sum\limits_{n}{\omega^{n}{{\log_{2}\left( {1 + {\frac{1}{\overset{\_}{\gamma}\Gamma}\frac{g_{k}^{n,n}{s_{k}^{n}(i)}}{{\sum\limits_{m \neq n}{g_{k}^{n,m}{s_{k}^{m}(i)}}} + \sigma_{k}^{2}}}} \right)}.}}}}}} & (20)\end{matrix}$

This allows solving the dual problem

$\begin{matrix}\begin{matrix}{\max\limits_{\omega^{n},{\lambda^{n}{\forall{n \in _{i}}}}}\min\limits_{{s_{k}^{n}{(i)}}{\forall{n \in _{i,k}}}}} & \Lambda & \; \\{s.t.} & {\omega^{n},{\lambda^{n} \geq 0}} & {\forall n} \\\; & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {{\forall n},k}\end{matrix} & (21)\end{matrix}$

of the problem according to equation (14) by solving K independentsub-problems

$\begin{matrix}\begin{matrix}\min\limits_{{s_{k}^{n}{(i)}}{\forall{n \in _{i}}}} & \Lambda_{k} & \; \\{s.t.} & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {\forall n}\end{matrix} & (22)\end{matrix}$

per Lagrange multiplier search step, thus rendering the overallalgorithm complexity linear in K.

As Λ_(k) is non-convex, minimization may however still require anexhaustive search with exponential complexity in the number of users N.For the rate-adaptive spectrum management problem, [P. Tsiaflakis, J.Vangorp, M. Moonen and J. Verlinden: Convex Relaxation BasedLow-Complexity Optimal Spectrum Balancing for Multi-User DSL. InAcoustics, Speech and Signal Processing, 2007, ICASSP 2007. IEEEInternational Conference, volume 3, pages II-349 to III-352, April 2007]suggests an efficient algorithm based on convex relaxation by notingthat the Lagrangian can be rewritten as a difference of convex (d.c.)functions. Rewriting Λ_(k) as

$\begin{matrix}{\Lambda_{k} = {{\sum\limits_{n}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - 1} \right)^{2}} + {\sum\limits_{n}{\lambda^{n}{s_{k}^{n}(i)}\underset{\underset{A}{}}{{- f_{s}}{\sum\limits_{n}{\omega^{n}{\log_{2}\left( {{\sum\limits_{m \neq n}{g_{k}^{n,m}{s_{k}^{m}(i)}}} + \sigma_{k}^{2} + \frac{g_{k}^{n,n}{s_{k}^{n}(i)}}{\overset{¨}{\gamma}\Gamma}} \right)}}}}}} + \underset{\underset{B}{}}{f_{s}{\sum\limits_{n}{\omega^{n}{\log_{2}\left( {\sum\limits_{m \neq n}{g_{k}^{n,m}{s_{k}^{m}(i)}\sigma_{k}^{2}}} \right)}}}}}} & (23)\end{matrix}$

where part A is a convex and part B is a concave portion. Hence, theproblem according to equation (14) exposes a d.c. structure and can thusbe solved using the approach as described in [P. Tsiaflakis, J. Vangorp,M. Moonen and J. Verlinden: Convex Relaxation Based Low-ComplexityOptimal Spectrum Balancing for Multi-User DSL. In Acoustics, Speech andSignal Processing, 2007, ICASSP 2007. IEEE International Conference,volume 3, pages II-349 to III-352, April 2007].

The solution for the per-tone sub-problem pursuant to equation (22) canbe approximated by iteratively solving a sequence of relaxed convexminimization problems, wherein the solution of one iteration is used asan approximation point for finding a convex relaxation of Λ_(k) in thenext iteration. An adaption of the low-complexity algorithm to theoptimization problem according to equation (14) can be realizedaccordingly.

Further Advantages:

The approach presented guarantees a minimum SNR margin for each userduring each (intermediate) stage of an iterative optimization of thepower allocation towards a target values s_(new). Hence, by ensuringsuch minimum SNR margin, the service stability can be significantlyimproved as the DSM system can be well protected against fluctuations ofnoise that is not managed by the DSM system (i.e. the SMC). In addition,forced re-configuration or re-training of users that are already inshow-time and hence service interruptions can be largely avoided.

LIST OF ACRONYMS

-   -   BER Bit Error Rate    -   CPE Customer Premises Equipment (DSL modem)    -   d.c. difference of convex    -   DMT Discrete Multi-Tone    -   DSL Digital Subscriber Line    -   DSLAM DSL Access Multiplexer    -   DSM Dynamic Spectrum Management    -   PSD Power Spectrum Density    -   SMC Spectrum Management Center    -   SNR Signal-to-Noise Ratio

1. A method for adjusting a power allocation of users in a digitalsubscriber line environment, the method comprising: determining anintermediate power allocation for at least one user initializing withthe digital subscriber line environment based on a new power allocationdetermined for the digital subscriber line environment containing the atleast one user; the intermediate power allocation providing a predefinedminimum signal-to-noise ratio (SNR) margin for active users of thedigital subscriber line environment.
 2. The method according to claim 1,which further comprises determining at least one intermediate powerallocation that converges towards the new power allocation.
 3. Themethod according to claim 1, wherein the digital subscriber lineenvironment contains at least one dynamic spectrum management system,which is managed by a spectrum management center.
 4. The methodaccording to claim 1, wherein the predefined minimum SNR margin isprovided for the intermediate power allocation or individually for eachof the users for which the intermediate power allocation is determined,for every subcarrier, a portion of the users or a portion of thesubcarriers.
 5. The method according to claim 1, which further comprisesdetermining the intermediate power allocation utilizing spectrallimitation masks as well as a limited power budget per the at least oneuser, the limited power budget being distributed among tones of adiscrete multi-tone modulation scheme.
 6. The method according to claim1, which further comprises determining the intermediate power allocationsuch that a distance metric between an actual power allocation and thenew power allocation is reduced.
 7. The method according to claim 6,wherein the distance metric is reduced meeting at least one of thefollowing constraints: a total transmit power is limited; a transmitpower on each sub-carrier or tone is limited individually by a powerspectrum density mask; and for the minimum SNR margin, a data rateachieved by each of the users with an obtained power allocation equalsor exceeds a predetermined target data rate.
 8. The method according toclaim 6, wherein the distance metric according to Δ(s(i), s_(new))comprises at least one property selected from the group consisting of: Δis convex in s_(k) ^(n); Δ is separable in s_(k) ^(n); and Δ(s(i),s_(new)) has a unique global minimum for s(i)=s_(new).
 9. The methodaccording to claim 6, wherein the distance metric comprises a distancefunction selected from the group consisting of:${{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - 1} \right)^{2}}}};$${{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}{\alpha_{k}^{n}\left( {{s_{k}^{n}(i)} - s_{k,{new}}^{n}} \right)}^{2}}}};{and}$${{\Delta \left( {{s(i)},s_{new}} \right)} = {\sum\limits_{n}{\sum\limits_{k}{\alpha_{k}^{n}\left( {\frac{s_{k}^{n5}(i)}{s_{k,{new}}^{n}} - \frac{s_{k,{new}}^{n}}{s_{k}^{n}(i)}} \right)}^{2}}}};$wherein s_(k) ^(n) denotes a power spectrum density of a transmit signalof a user n; k denotes a subchannel or tone; s_(new) is the new powerallocation; and s(i) is the intermediate power allocation at a step i.10. The method according to claim 1, wherein the intermediate powerallocation is determined by solving a following optimization problem:$\begin{matrix}\min\limits_{{s_{k}^{n}{(i)}}{\forall{n \in _{i,k}}}} & {\Delta \left( {{s(i)},s_{new}} \right)} & \; \\{s.t.} & {{R^{n}\left( \overset{\_}{\gamma} \right)}_{s{(i)}}{\geq R_{target}^{n}}} & {\forall n} \\\; & {{\sum\limits_{k}{s_{k}^{n}(i)}} \leq P_{\max}^{n}} & {\forall n} \\\; & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {{\forall n},k}\end{matrix}$ wherein n∈G_(i) ⊂N is the user; G_(i) denotes a groupcontaining the at least one user initializing with the digitalsubscriber line environment; N denotes the users sharing a same binder;s_(k) ^(n) denotes a power spectrum density of a transmit signal of auser n; s_(k,mask) ^(n) is a PSD mask determined by a band profile used;k determines a subchannel or tone; s_(new) is the new power allocation;s(i) is the intermediate power allocation at a step i; γ is thepredefined minimum SNR margin; R^(n) is a data rate of the user n;R_(target) ^(n) is a target data rate of user n; and P_(max) ^(n) is amaximum aggregate transmit power of the user n.
 11. The method accordingto claim 10, which further comprises solving the optimization problemvia a dual decomposition combined with a convex relaxation.
 12. Themethod according to claim 11, which further comprises solving theoptimization problem by decomposing a Lagrangian$\Lambda = {{\Delta \left( {{s(i)},s_{new}} \right)} + {\sum\limits_{n}{\omega^{n}\left( {R_{target}^{n} - {R^{n}(i)}} \right)}} + {\sum\limits_{n}{\lambda^{n}\left( {{\sum\limits_{k}{s_{k}^{n}(i)}} - P_{\max}^{n}} \right)}}}$wherein ω^(n) is a dual variable corresponding to a data rate constraintof the user n; and λ^(n) is a dual variable corresponding to a powerconstraint, into per-tone Lagrangians Λ_(k) according to$\mspace{79mu} {\Lambda = {{\sum\limits_{k}\Lambda_{k}} + \underset{\underset{{{const}.\mspace{14mu} {in}}\mspace{14mu} {s{(i)}}}{}}{{\sum\limits_{n}{\omega^{n}R_{target}^{n}}} - {\sum\limits_{n}{\lambda^{n}P_{\max}^{n}}}}}}$     with$\Lambda_{k} = {{\sum\limits_{n}\left( {\frac{s_{k}^{n}(i)}{s_{k,{new}}^{n}} - 1} \right)^{2}} + {\sum\limits_{n}{\lambda^{n}{s_{k}^{n}(i)}}} - {f_{s}{\sum\limits_{n}{\omega^{n}{{\log_{2}\left( {1 + {\frac{1}{\overset{¨}{\gamma}\Gamma}\frac{g_{k}^{n,n}{s_{k}^{n}(i)}}{{\sum\limits_{m \neq n}{g_{k}^{n,m}(i)}} + \sigma_{k}^{2}}}} \right)}.}}}}}$13. The method according to claim 12, wherein a dual problem$\begin{matrix}{\max\limits_{\omega^{n},{\lambda^{n}{\forall{n \in _{i}}}}}\min\limits_{{{s_{k}^{n}{(i)}}{\forall{n \in _{i}}}},k}} & \Lambda & \; \\{s.t.} & {\omega^{n},{\lambda^{n} \geq 0}} & {\forall n} \\\; & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {{\forall n},k}\end{matrix}$ of the optimization problem is solved by solving Kindependent sub-problems $\begin{matrix}\min\limits_{{s_{k}^{n}{(i)}}{\forall{n \in _{i}}}} & \Lambda_{k} & \; \\{s.t.} & {0 \leq {s_{k}^{n}(i)} \leq s_{k,{mask}}^{n}} & {\forall n}\end{matrix}$ per Lagrange multiplier search step.
 14. The methodaccording to claim 10, wherein: at an initial step i=0, it is determinedwhether the minimum SNR margin γ with 1≦ γ≦γ_(target) exists so that theoptimization problem is feasible for s(0); in case where the minimum SNRmargin γ exists, the value is used to determine the at least oneintermediate power allocation; in case no such minimum SNR margin γ≧1exists, a set G₀ is augmented by at least one additional user whosepower allocation is re-shaped at the time instant t=t₀.
 15. The methodaccording to claim 1, which further comprises determining theintermediate power allocation such that a distance metric between anactual power allocation and the new power allocation is minimized.
 16. Adevice, comprising: a processing unit programmed to adjust a powerallocation of users in a digital subscriber line environment bydetermining an intermediate power allocation for at least one userinitializing with the digital subscriber line environment based on a newpower allocation determined for the digital subscriber line environmentcontaining the at least one user; the intermediate power allocationproviding a predefined minimum signal-to-noise ratio margin for activeusers of the digital subscriber line environment.
 17. The deviceaccording to claim 16, wherein the device is selected from the groupconsisting of a modem, a digital subscriber line access multiplexer, acentralized network component, and a spectrum management center.
 18. Amethod for adjusting a power allocation of users in a digital subscriberline environment, the method comprising: upon receiving a request by anew user to be initialized to the digital subscriber line environment,determining an intermediate power allocation for the new userinitializing with the digital subscriber line environment based on a newpower allocation determined for the digital subscriber line environmentcontaining the new user; the intermediate power allocation providing fora predefined minimum signal-to-noise ratio margin for active users ofthe digital subscriber line environment.